zoomableinteractivetimeseriesvisualizationvis.berkeley.edu/courses/cs294-10-fa13/wiki/images/d/d5/mitar-poster.pdfzoomableinteractivetimeseriesvisualization...

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Zoomable Interactive Time Series Visualization Mitar Milutinović ([email protected]) Problem concurrent visualization of multiple time series datasets in the browser interactive, zoomable, minimal data transferred to the browser, support for huge datasets Motivation Internet of Things time series datasets are becoming more and more common sensors networks, citizen science measurements with mobile devices huge datasets, but trend of moving everything into the cloud comparison between data, but data is big, even one dataset can be incomprehensible and visualization crowded loss of information when zooming out Related work imMens: Real-time Visual Querying of Big Data Nanocubes for Real-Time Exploration of Spatiotemporal Datasets Horizon Graphs Stack Zooming for Multi-Focus Interaction in Time-Series Data Visual- ization Initial view Initial view. Time series navigator below for selecting. Two parallel time series on each chart, three charts in parallel. Design principles in the browser interactive, mouse interface scalable, RESTful API minimization of “operation mode” switching no need to understand the technical background of the underlying sys- tem Approach three components server side time series storage (Python + MongoDB) HTTP RESTful interface (Python + Django) client visualization (JavaScript + Highstock) layered downsampled datapoints at various granularity levels both value and time downsampling operators multiple downsampling operators at once user gets data from the granularity levels most suitable for the time- span requested derived time series from another time series selecting, panning, zooming, highlighting parallel inter-locked series on one chart, parallel inter-locked charts Future work client performance improvements other types of values supported graphs discrete events sharing of visualization – unique URL for each visualization configura- tion other types of visualizing time series data stacked graphs areas background color regions analyzing time series properties (auto-correlation) and exposing them Detail Zoomed view Highest detail zoom without range information. Range view Range around the mean, but no highlighting enabled.

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Page 1: ZoomableInteractiveTimeSeriesVisualizationvis.berkeley.edu/courses/cs294-10-fa13/wiki/images/d/d5/Mitar-Poster.pdfZoomableInteractiveTimeSeriesVisualization MitarMilutinović(mitar@tnode.com)

Zoomable Interactive Time Series VisualizationMitar Milutinović ([email protected])

Problem∙ concurrent visualization of multiple time series datasets in the browser∙ interactive, zoomable, minimal data transferred to the browser, support

for huge datasets

Motivation∙ Internet of Things time series datasets are becoming more and more

common∙ sensors networks, citizen science measurements with mobile devices∙ huge datasets, but trend of moving everything into the cloud∙ comparison between data, but data is big, even one dataset can be

incomprehensible and visualization crowded∙ loss of information when zooming out

Related work∙ imMens: Real-time Visual Querying of Big Data∙ Nanocubes for Real-Time Exploration of Spatiotemporal Datasets∙ Horizon Graphs∙ Stack Zooming for Multi-Focus Interaction in Time-Series Data Visual-

ization

Initial viewInitial view. Time series navigator below for selecting. Two parallel timeseries on each chart, three charts in parallel.

Design principles∙ in the browser∙ interactive, mouse interface∙ scalable, RESTful API∙ minimization of “operation mode” switching∙ no need to understand the technical background of the underlying sys-

tem

Approach∙ three components

– server side time series storage (Python + MongoDB)– HTTP RESTful interface (Python + Django)– client visualization (JavaScript + Highstock)

∙ layered downsampled datapoints at various granularity levels– both value and time downsampling operators– multiple downsampling operators at once– user gets data from the granularity levels most suitable for the time-

span requested∙ derived time series from another time series∙ selecting, panning, zooming, highlighting∙ parallel inter-locked series on one chart, parallel inter-locked charts

Future work∙ client performance improvements∙ other types of values supported

– graphs– discrete events

∙ sharing of visualization – unique URL for each visualization configura-tion

∙ other types of visualizing time series data– stacked graphs– areas– background color regions

∙ analyzing time series properties (auto-correlation) and exposing them

Detail

Zoomed viewHighest detail zoom without range information.

Range viewRange around the mean, but no highlighting enabled.